Results food data clustering DEL- 25/May/2020

All Data clusters (Deep learning, DEL (Deep Embedding Clustering layer))

resultft_DEL_all_5 <- read.csv('/Users/xbasra/Documents/Data/Clustering_Food_Alergies/Intermediate/CsvData_Output/resultft_DEL_all_5_cluster.csv')
# replacing the empty space "" values with no as done in the main analysis file
resultft_DEL_all_5$farmlive[resultft_DEL_all_5$farmlive == ""] <- NA
resultft_DEL_all_5 <-  resultft_DEL_all_5 %>% replace_na (list(farmlive = 'no'))
#tsne_converted_food$cl_DEL <- factor(resultft_DEL_all$cluster)
#ggplot(tsne_converted_food, aes(x=X, y=Y, color=cl_DEL)) + geom_point()
resultft_DEL_all_5$cluster <- as.factor(resultft_DEL_all_5$cluster)

DEC_Embedding_5 = read.csv('/Users/xbasra/Documents/Data/Clustering_Food_Alergies/Intermediate/CsvData_Output/DEC_Embedding_5.csv')

set.seed(10)
#tsne_converted_food_DEL <- Rtsne(X = EDL_Embedding ,perplexity= 200, is_distance = FALSE, check_duplicates = FALSE)
tsne_converted_food_DEC_5 <- Rtsne(X = DEC_Embedding_5 ,perplexity= 150, is_distance = FALSE, check_duplicates = FALSE)
tsne_converted_food_DEC_5 <- tsne_converted_food_DEC_5$Y %>%
  data.frame() %>%
  setNames(c("X", "Y"))
tsne_converted_food_DEC_5$cl <- factor(resultft_DEL_all_5$cluster)
ggplot(tsne_converted_food_DEC_5, aes(x=X, y=Y, color=cl)) + geom_point()

tsne_converted_food_DEC_3d_5 <- Rtsne(X = DEC_Embedding_5 ,perplexity= 150, dims = 3, is_distance = FALSE, check_duplicates = FALSE)
tsne_converted_food_DEC_3d_5 <- tsne_converted_food_DEC_3d_5$Y %>%
  data.frame() %>%
  setNames(c("X", "Y", "Z"))
tsne_converted_food_DEC_3d_5$cl <- factor(resultft_DEL_all_5$cluster)
p <- plot_ly(tsne_converted_food_DEC_3d_5, x = ~X, y = ~Y, z = ~Z, color = ~cl, colors = c('#BF382A', '#0C4B8E')) %>%
  add_markers() %>%
  layout(scene = list(xaxis = list(title = 'Dim1'),
                     yaxis = list(title = 'Dim2'),
                     zaxis = list(title = 'Dim3')))
p

Density plot shoiwing the age distribution for each cluster

resultft_DEL_all$cluster <- as.factor(resultft_DEL_all_5$cluster)
age_g <- ggplot(resultft_DEL_all_5, aes(sIgE_f3))
age_p <- age_g + geom_density(aes(fill=factor(cluster)), alpha=0.8) +
    labs(title="Density plot",
         subtitle="sIgE_f1 of persons Grouped by Clusters",
         caption="Source: Source: results of Hierarchical clustering with tree-based distance and distance d1",
         x="sIgE_f1",
         fill="# Clusters")
ggplotly(age_p)

g <- ggplot(resultft_DEL_all_5, aes(bmi2)) + scale_fill_brewer(palette = "Spectral")
s <- g + geom_histogram(aes(fill=factor(cluster)), 
                   bins=5, 
                   col="black", 
                   size=.1) +   # change number of bins
  labs(title="Histogram with Fixed Bins", 
       subtitle="Age across different clusters",
       x="Age",
         fill="# Clusters") 
ggplotly(s)

table_uft_DEL_all <- tableby(cluster ~ ., data = as.list(resultft_DEL_all_5))
summary(table_uft_DEL_all, title = "Charachtaristcs of Clusters")

Table: Charachtaristcs of Clusters

	0 (N=773)	1 (N=711)	2 (N=216)	3 (N=53)	4 (N=119)	Total (N=1872)	p value
sIgE_f1							< 0.001
Mean (SD)	0.004 (0.043)	0.000 (0.000)	0.084 (0.257)	0.099 (0.227)	1.074 (6.866)	0.082 (1.747)
Range	0.000 - 0.626	0.000 - 0.000	0.000 - 2.857	0.000 - 1.032	0.000 - 73.692	0.000 - 73.692
sIgE_f2							< 0.001
Mean (SD)	0.001 (0.009)	0.000 (0.000)	0.112 (0.228)	0.089 (0.223)	0.699 (2.089)	0.060 (0.558)
Range	0.000 - 0.160	0.000 - 0.000	0.000 - 1.091	0.000 - 1.280	0.000 - 13.623	0.000 - 13.623
sIgE_f3							< 0.001
Mean (SD)	0.000 (0.004)	0.000 (0.000)	0.012 (0.023)	0.104 (0.259)	0.074 (0.186)	0.009 (0.069)
Range	0.000 - 0.052	0.000 - 0.000	0.000 - 0.137	0.000 - 1.080	0.000 - 1.332	0.000 - 1.332
sIgE_f4							< 0.001
Mean (SD)	0.001 (0.006)	0.000 (0.000)	0.047 (0.125)	0.193 (0.321)	0.966 (1.890)	0.073 (0.534)
Range	0.000 - 0.090	0.000 - 0.000	0.000 - 1.129	0.000 - 1.280	0.000 - 12.512	0.000 - 12.512
sIgE_f13							< 0.001
Mean (SD)	0.003 (0.019)	0.009 (0.056)	0.141 (0.190)	1.104 (2.873)	4.282 (18.801)	0.324 (4.861)
Range	0.000 - 0.411	0.000 - 0.726	0.000 - 1.017	0.008 - 16.776	0.000 - 149.746	0.000 - 149.746
sIgE_f14							< 0.001
Mean (SD)	0.000 (0.002)	0.000 (0.000)	0.011 (0.034)	0.080 (0.140)	0.670 (1.761)	0.046 (0.472)
Range	0.000 - 0.030	0.000 - 0.000	0.000 - 0.310	0.000 - 0.462	0.000 - 12.386	0.000 - 12.386
sIgE_f17							< 0.001
Mean (SD)	0.026 (0.150)	0.058 (0.215)	2.554 (2.258)	6.440 (4.758)	20.201 (21.721)	1.794 (7.461)
Range	0.000 - 1.619	0.000 - 1.715	0.000 - 8.681	0.000 - 13.119	0.000 - 111.259	0.000 - 111.259
sIgE_f18							< 0.001
Mean (SD)	0.001 (0.012)	0.002 (0.026)	0.036 (0.175)	0.094 (0.398)	0.529 (4.297)	0.042 (1.091)
Range	0.000 - 0.322	0.000 - 0.686	0.000 - 1.744	0.000 - 2.901	0.000 - 46.879	0.000 - 46.879
sIgE_f20							< 0.001
Mean (SD)	0.002 (0.011)	0.003 (0.014)	0.085 (0.110)	0.214 (0.225)	1.031 (1.638)	0.083 (0.485)
Range	0.000 - 0.138	0.000 - 0.153	0.000 - 0.945	0.000 - 1.294	0.000 - 9.959	0.000 - 9.959
sIgE_f36							< 0.001
Mean (SD)	0.002 (0.012)	0.004 (0.014)	0.053 (0.057)	0.152 (0.206)	0.409 (1.041)	0.039 (0.283)
Range	0.000 - 0.209	0.000 - 0.120	0.000 - 0.321	0.000 - 1.051	0.000 - 7.754	0.000 - 7.754
gender2							0.005
females	423 (54.7%)	416 (58.5%)	97 (44.9%)	24 (45.3%)	62 (52.1%)	1022 (54.6%)
males	350 (45.3%)	295 (41.5%)	119 (55.1%)	29 (54.7%)	57 (47.9%)	850 (45.4%)
age							< 0.001
Mean (SD)	62.134 (8.549)	37.242 (9.728)	46.215 (15.539)	40.945 (13.208)	42.437 (14.837)	48.991 (15.551)
Range	30.006 - 77.746	18.146 - 64.264	19.266 - 76.190	20.420 - 75.003	19.058 - 78.075	18.146 - 78.075
bmi2							< 0.001
Mean (SD)	28.285 (4.765)	24.891 (3.742)	25.902 (3.947)	25.977 (4.125)	25.954 (4.534)	26.507 (4.540)
Range	16.975 - 50.058	17.404 - 41.007	18.290 - 41.197	19.493 - 37.950	17.915 - 38.514	16.975 - 50.058
farmlive
	0 (0.0%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	0 (0.0%)
no	632 (81.8%)	655 (92.1%)	197 (91.2%)	50 (94.3%)	114 (95.8%)	1648 (88.0%)
yes	141 (18.2%)	56 (7.9%)	19 (8.8%)	3 (5.7%)	5 (4.2%)	224 (12.0%)
family_allergy_hist							< 0.001
no	566 (73.2%)	297 (41.8%)	106 (49.1%)	16 (30.2%)	37 (31.1%)	1022 (54.6%)
yes	207 (26.8%)	414 (58.2%)	110 (50.9%)	37 (69.8%)	82 (68.9%)	850 (45.4%)

# adding the id variable 
#result_food_uft_DEL_k$ID <- food_data_id$ID 
#write.csv(result_food_uft_DEL_k, "/Users/xbasra/Documents/Data/Clustering_Food_Alergies/CsvData/result_food_uft_DEL_k.csv")

Charachtiristic Analysis

resultft_DEL_all_5$cluster <- as.factor(resultft_DEL_all_5$cluster)
catdes(resultft_DEL_all_5, 16)

Link between the cluster variable and the categorical variables (chi-square test)
=================================================================================
                         p.value df
family_allergy_hist 1.462223e-41  4
farmlive            2.177886e-10  4
gender2             5.296437e-03  4

Description of each cluster by the categories
=============================================
$`0`
                         Cla/Mod  Mod/Cla   Global      p.value     v.test
family_allergy_hist=no  55.38160 73.22122 54.59402 5.241366e-43  13.747922
farmlive=yes            62.94643 18.24062 11.96581 3.836394e-12   6.943081
farmlive=no             38.34951 81.75938 88.03419 3.836394e-12  -6.943081
family_allergy_hist=yes 24.35294 26.77878 45.40598 5.241366e-43 -13.747922

$`1`
                         Cla/Mod   Mod/Cla   Global      p.value    v.test
family_allergy_hist=yes 48.70588 58.227848 45.40598 2.776694e-18  8.720217
farmlive=no             39.74515 92.123769 88.03419 1.296541e-05  4.360688
gender2=females         40.70450 58.509142 54.59402 7.755781e-03  2.662521
gender2=males           34.70588 41.490858 45.40598 7.755781e-03 -2.662521
farmlive=yes            25.00000  7.876231 11.96581 1.296541e-05 -4.360688
family_allergy_hist=no  29.06067 41.772152 54.59402 2.776694e-18 -8.720217

$`2`
                  Cla/Mod  Mod/Cla   Global     p.value    v.test
gender2=males   14.000000 55.09259 45.40598 0.002480136  3.025754
gender2=females  9.491194 44.90741 54.59402 0.002480136 -3.025754

$`3`
                         Cla/Mod  Mod/Cla   Global      p.value    v.test
family_allergy_hist=yes 4.352941 69.81132 45.40598 0.0003159048  3.601896
family_allergy_hist=no  1.565558 30.18868 54.59402 0.0003159048 -3.601896

$`4`
                         Cla/Mod   Mod/Cla   Global      p.value    v.test
family_allergy_hist=yes 9.647059 68.907563 45.40598 1.046986e-07  5.318374
farmlive=no             6.917476 95.798319 88.03419 3.155607e-03  2.952159
farmlive=yes            2.232143  4.201681 11.96581 3.155607e-03 -2.952159
family_allergy_hist=no  3.620352 31.092437 54.59402 1.046986e-07 -5.318374


Link between the cluster variable and the quantitative variables
================================================================
               Eta2       P-value
age      0.53459417 4.168803e-308
sIgE_f17 0.44312635 1.912237e-235
sIgE_f20 0.26721574 2.259101e-124
sIgE_f4  0.19429220  4.761183e-86
sIgE_f36 0.12646074  1.831810e-53
sIgE_f3  0.12461333  1.297269e-52
sIgE_f14 0.11938658  3.221263e-50
bmi2     0.11488752  3.609795e-48
sIgE_f2  0.09332546  1.682564e-38
sIgE_f13 0.04646742  2.274499e-18
sIgE_f1  0.02219638  1.724935e-08
sIgE_f18 0.01388032  3.006808e-05

Description of each cluster by quantitative variables
=====================================================
$`0`
            v.test Mean in category Overall mean sd in category  Overall sd       p.value
age      30.668195     6.213375e+01 48.990817991    8.543407112 15.54647228 1.511905e-206
bmi2     14.206408     2.828456e+01 26.507217851    4.762205738  4.53851342  8.360568e-46
sIgE_f13 -2.400902     2.783943e-03  0.324389665    0.019354127  4.85933840  1.635472e-02
sIgE_f14 -3.537504     1.723239e-04  0.046205234    0.001900249  0.47206221  4.039274e-04
sIgE_f2  -3.857459     8.040704e-04  0.060153551    0.009378138  0.55814025  1.145717e-04
sIgE_f3  -4.688430     3.528329e-04  0.009219938    0.003741759  0.06860917  2.753086e-06
sIgE_f36 -4.715205     1.980466e-03  0.038784940    0.011657685  0.28315734  2.414673e-06
sIgE_f4  -4.889479     5.302067e-04  0.072516311    0.005758889  0.53408927  1.011030e-06
sIgE_f20 -6.109043     1.752470e-03  0.083349557    0.010506697  0.48453963  1.002306e-09
sIgE_f17 -8.598199     2.595266e-02  1.793797158    0.149831424  7.45872089  8.097668e-18

$`1`
             v.test Mean in category Overall mean sd in category  Overall sd       p.value
sIgE_f13  -2.195853      0.009161681  0.324389665     0.05561821  4.85933840  2.810249e-02
sIgE_f14  -3.313199      0.000000000  0.046205234     0.00000000  0.47206221  9.223532e-04
sIgE_f2   -3.648157      0.000000000  0.060153551     0.00000000  0.55814025  2.641283e-04
sIgE_f36  -4.167325      0.003924759  0.038784940     0.01380475  0.28315734  3.081945e-05
sIgE_f3   -4.548848      0.000000000  0.009219938     0.00000000  0.06860917  5.394044e-06
sIgE_f4   -4.595973      0.000000000  0.072516311     0.00000000  0.53408927  4.307352e-06
sIgE_f20  -5.589043      0.003345652  0.083349557     0.01379930  0.48453963  2.283241e-08
sIgE_f17  -7.878923      0.057693637  1.793797158     0.21479644  7.45872089  3.302154e-15
bmi2     -12.056213     24.890743000 26.507217851     3.73894961  4.53851342  1.798648e-33
age      -25.581075     37.241975892 48.990817991     9.72107748 15.54647228 2.477828e-144

$`2`
        v.test Mean in category Overall mean sd in category Overall sd     p.value
bmi2 -2.082651         25.90216     26.50722       3.937503   4.538513 0.037283043
age  -2.789666         46.21462     48.99082      15.503033  15.546472 0.005276239

$`3`
            v.test Mean in category Overall mean sd in category  Overall sd      p.value
sIgE_f3  10.194439        0.1039498  0.009219938      0.2568479  0.06860917 2.099535e-24
sIgE_f17  4.599242        6.4399356  1.793797158      4.7126062  7.45872089 4.240308e-06
sIgE_f36  2.949079        0.1518832  0.038784940      0.2040307  0.28315734 3.187226e-03
sIgE_f20  1.998084        0.2144743  0.083349557      0.2228088  0.48453963 4.570757e-02
age      -3.821272       40.9447943 48.990817991     13.0824425 15.54647228 1.327652e-04

$`4`
            v.test Mean in category Overall mean sd in category  Overall sd       p.value
sIgE_f17 27.813053      20.20124627  1.793797158      21.629315  7.45872089 3.015940e-170
sIgE_f20 22.037930       1.03085274  0.083349557       1.631123  0.48453963 1.247109e-107
sIgE_f4  18.862142       0.96640914  0.072516311       1.881997  0.53408927  2.335618e-79
sIgE_f14 14.894169       0.67007808  0.046205234       1.753952  0.47206221  3.596293e-50
sIgE_f36 14.751227       0.40941150  0.038784940       1.036971  0.28315734  3.021231e-49
sIgE_f2  12.892064       0.69863218  0.060153551       2.080167  0.55814025  4.989076e-38
sIgE_f3  10.637942       0.07398196  0.009219938       0.185565  0.06860917  1.984654e-26
sIgE_f13  9.178780       4.28208805  0.324389665      18.721848  4.85933840  4.360025e-20
sIgE_f1   6.401634       1.07441269  0.082481475       6.837547  1.74626497  1.537229e-10
sIgE_f18  5.043438       0.52941789  0.041507056       4.279045  1.09026788  4.572417e-07
age      -4.751317      42.43651669 48.990817991      14.774762 15.54647228  2.020965e-06

Random Data clusters with DEL (Deep Embedding Clustering layer)

#result_rand_uft_DEL_k <- read.csv("/Users/xbasra/Documents/Data/Clustering_Food_Alergies/Intermediate/CsvData_Output/result_rand_food_uft_DEL_k.csv")
result_rand_uft_DEL_k <- read.csv("/Users/xbasra/Documents/Data/Clustering_Food_Alergies/Intermediate/CsvData_Output/result_rand_uft_DEL_k.csv")
result_rand_uft_DEL_k$farmlive[result_rand_uft_DEL_k$farmlive == ""] <- NA
result_rand_uft_DEL_k <-  result_rand_uft_DEL_k %>% replace_na (list(farmlive = 'no'))
table_rand_uft_DEL_k <- tableby(cluster ~ ., data = as.list(result_rand_uft_DEL_k))
summary(table_rand_uft_DEL_k, title = "Charachtaristcs of Clusters")

Table: Charachtaristcs of Clusters

	0 (N=49)	1 (N=482)	2 (N=28)	3 (N=104)	4 (N=440)	Total (N=1103)	p value
sIgE_f1							< 0.001
Mean (SD)	0.083 (0.196)	0.000 (0.000)	0.191 (0.540)	0.083 (0.189)	0.000 (0.000)	0.016 (0.117)
Range	0.000 - 1.032	0.000 - 0.000	0.000 - 2.845	0.000 - 0.990	0.000 - 0.000	0.000 - 2.845
sIgE_f2							< 0.001
Mean (SD)	0.113 (0.403)	0.000 (0.000)	0.579 (1.506)	0.109 (0.225)	0.000 (0.000)	0.030 (0.277)
Range	0.000 - 2.750	0.000 - 0.000	0.000 - 6.849	0.000 - 1.091	0.000 - 0.000	0.000 - 6.849
sIgE_f3							< 0.001
Mean (SD)	0.021 (0.038)	0.000 (0.000)	0.043 (0.062)	0.012 (0.020)	0.000 (0.000)	0.003 (0.016)
Range	0.000 - 0.213	0.000 - 0.000	0.000 - 0.211	0.000 - 0.080	0.000 - 0.000	0.000 - 0.213
sIgE_f4							< 0.001
Mean (SD)	0.281 (0.581)	0.000 (0.000)	0.773 (1.718)	0.036 (0.076)	0.000 (0.000)	0.035 (0.324)
Range	0.000 - 2.543	0.000 - 0.000	0.000 - 8.417	0.000 - 0.428	0.000 - 0.000	0.000 - 8.417
sIgE_f13							< 0.001
Mean (SD)	0.517 (0.548)	0.002 (0.030)	5.907 (25.114)	0.130 (0.190)	0.002 (0.020)	0.187 (4.042)
Range	0.013 - 1.957	0.000 - 0.642	0.000 - 133.659	0.000 - 1.017	0.000 - 0.411	0.000 - 133.659
sIgE_f14							< 0.001
Mean (SD)	0.112 (0.215)	0.000 (0.000)	0.744 (1.782)	0.008 (0.020)	0.000 (0.000)	0.025 (0.306)
Range	0.000 - 0.833	0.000 - 0.000	0.000 - 8.505	0.000 - 0.160	0.000 - 0.000	0.000 - 8.505
sIgE_f17							< 0.001
Mean (SD)	6.966 (5.245)	0.013 (0.086)	27.282 (21.898)	1.724 (1.641)	0.010 (0.082)	1.174 (5.760)
Range	0.000 - 20.156	0.000 - 1.014	0.000 - 76.467	0.000 - 6.215	0.000 - 1.011	0.000 - 76.467
sIgE_f18							< 0.001
Mean (SD)	0.103 (0.415)	0.002 (0.031)	1.830 (8.835)	0.029 (0.165)	0.001 (0.015)	0.055 (1.416)
Range	0.000 - 2.901	0.000 - 0.686	0.000 - 46.879	0.000 - 1.678	0.000 - 0.322	0.000 - 46.879
sIgE_f20							< 0.001
Mean (SD)	0.301 (0.286)	0.001 (0.004)	1.251 (1.827)	0.066 (0.077)	0.001 (0.005)	0.052 (0.357)
Range	0.000 - 1.294	0.000 - 0.041	0.000 - 9.959	0.000 - 0.527	0.000 - 0.057	0.000 - 9.959
sIgE_f36							< 0.001
Mean (SD)	0.174 (0.222)	0.001 (0.006)	0.512 (1.466)	0.053 (0.054)	0.001 (0.007)	0.027 (0.250)
Range	0.000 - 1.051	0.000 - 0.056	0.000 - 7.754	0.000 - 0.238	0.000 - 0.067	0.000 - 7.754
gender2							< 0.001
females	21 (42.9%)	317 (65.8%)	14 (50.0%)	48 (46.2%)	183 (41.6%)	583 (52.9%)
males	28 (57.1%)	165 (34.2%)	14 (50.0%)	56 (53.8%)	257 (58.4%)	520 (47.1%)
age							< 0.001
Mean (SD)	43.733 (13.832)	40.954 (12.001)	39.981 (14.744)	48.435 (15.603)	62.643 (9.183)	50.410 (15.390)
Range	20.867 - 77.130	18.146 - 73.475	21.217 - 70.735	19.266 - 75.949	26.511 - 77.746	18.146 - 77.746
bmi2							< 0.001
Mean (SD)	26.104 (4.237)	24.543 (3.447)	25.762 (4.977)	26.526 (4.329)	27.743 (4.054)	26.107 (4.127)
Range	20.069 - 37.950	17.404 - 42.768	18.939 - 37.545	19.223 - 41.007	16.975 - 44.816	16.975 - 44.816
farmlive
	0 (0.0%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	0 (0.0%)
no	46 (93.9%)	444 (92.1%)	28 (100.0%)	99 (95.2%)	343 (78.0%)	960 (87.0%)
yes	3 (6.1%)	38 (7.9%)	0 (0.0%)	5 (4.8%)	97 (22.0%)	143 (13.0%)
family_allergy_hist							< 0.001
no	19 (38.8%)	223 (46.3%)	6 (21.4%)	62 (59.6%)	385 (87.5%)	695 (63.0%)
yes	30 (61.2%)	259 (53.7%)	22 (78.6%)	42 (40.4%)	55 (12.5%)	408 (37.0%)

# adding the id variable 
#result_food_uft_DEL_k$ID <- food_data_id$ID 
#write.csv(result_food_uft_DEL_k, "/Users/xbasra/Documents/Data/Clustering_Food_Alergies/CsvData/result_food_uft_DEL_k.csv")

Charachtiristic Analysis

result_rand_uft_DEL_k$cluster <- as.factor(result_rand_uft_DEL_k$cluster)
#result_food_uft_DEL_k <- result_food_uft_DEL_k[-c(1,2,20)]
catdes(result_rand_uft_DEL_k, 16)

Link between the cluster variable and the categorical variables (chi-square test)
=================================================================================
                         p.value df
family_allergy_hist 3.424012e-43  4
gender2             5.745123e-12  4
farmlive            2.530325e-11  4

Description of each cluster by the categories
=============================================
$`0`
                         Cla/Mod  Mod/Cla   Global      p.value    v.test
family_allergy_hist=yes 7.352941 61.22449 36.99003 0.0004907976  3.485729
family_allergy_hist=no  2.733813 38.77551 63.00997 0.0004907976 -3.485729

$`1`
                         Cla/Mod   Mod/Cla   Global      p.value     v.test
family_allergy_hist=yes 63.48039 53.734440 36.99003 2.903413e-24  10.162890
gender2=females         54.37393 65.767635 52.85585 2.998922e-14   7.598366
farmlive=no             46.25000 92.116183 87.03536 6.721713e-06   4.502315
farmlive=yes            26.57343  7.883817 12.96464 6.721713e-06  -4.502315
gender2=males           31.73077 34.232365 47.14415 2.998922e-14  -7.598366
family_allergy_hist=no  32.08633 46.265560 63.00997 2.903413e-24 -10.162890

$`2`
                          Cla/Mod   Mod/Cla   Global      p.value    v.test
family_allergy_hist=yes 5.3921569  78.57143 36.99003 7.660114e-06  4.474470
farmlive=no             2.9166667 100.00000 87.03536 1.944940e-02  2.336804
farmlive=yes            0.0000000   0.00000 12.96464 1.944940e-02 -2.336804
family_allergy_hist=no  0.8633094  21.42857 63.00997 7.660114e-06 -4.474470

$`3`
               Cla/Mod   Mod/Cla   Global     p.value    v.test
farmlive=no  10.312500 95.192308 87.03536 0.004857209  2.816354
farmlive=yes  3.496503  4.807692 12.96464 0.004857209 -2.816354

$`4`
                         Cla/Mod  Mod/Cla   Global      p.value     v.test
family_allergy_hist=no  55.39568 87.50000 63.00997 2.020566e-46  14.305542
farmlive=yes            67.83217 22.04545 12.96464 5.258224e-13   7.218453
gender2=males           49.42308 58.40909 47.14415 1.026148e-09   6.105289
gender2=females         31.38937 41.59091 52.85585 1.026148e-09  -6.105289
farmlive=no             35.72917 77.95455 87.03536 5.258224e-13  -7.218453
family_allergy_hist=yes 13.48039 12.50000 36.99003 2.020566e-46 -14.305542


Link between the cluster variable and the quantitative variables
================================================================
               Eta2       P-value
sIgE_f17 0.60196868 7.499421e-218
age      0.43899232 3.695744e-136
sIgE_f20 0.32563794  2.075189e-92
sIgE_f3  0.26464644  7.440968e-72
sIgE_f4  0.16694806  2.605188e-42
sIgE_f14 0.14940898  2.167347e-37
bmi2     0.12669886  3.528532e-31
sIgE_f2  0.12139732  9.383073e-30
sIgE_f36 0.12067931  1.460744e-29
sIgE_f1  0.11707576  1.338788e-28
sIgE_f13 0.05296825  3.179828e-12
sIgE_f18 0.04120260  2.194434e-09

Description of each cluster by quantitative variables
=====================================================
$`0`
            v.test Mean in category Overall mean sd in category  Overall sd      p.value
sIgE_f3   7.815142       0.02089372  0.003145542     0.03776886  0.01625494 5.490118e-15
sIgE_f17  7.200998       6.96621397  1.174252032     5.19134622  5.75707008 5.977324e-13
sIgE_f4   5.428826       0.28128416  0.035469421     0.57498788  0.32409368 5.672608e-08
sIgE_f20  4.990445       0.30061171  0.051857938     0.28312616  0.35677871 6.024033e-07
sIgE_f36  4.221718       0.17415762  0.026534870     0.22019235  0.25028371 2.424472e-05
sIgE_f1   4.067095       0.08298353  0.016341103     0.19364583  0.11728300 4.760291e-05
sIgE_f2   2.142614       0.11283843  0.029970671     0.39932637  0.27682810 3.214410e-02
sIgE_f14  2.053939       0.11248115  0.024610767     0.21325191  0.30621284 3.998155e-02
age      -3.106838      43.73298767 50.409945023    13.68964100 15.38255887 1.891003e-03

$`1`
             v.test Mean in category Overall mean sd in category  Overall sd      p.value
sIgE_f14  -2.350554     0.000000e+00  0.024610767    0.000000000  0.30621284 1.874548e-02
sIgE_f36  -2.977528     1.053667e-03  0.026534870    0.006484391  0.25028371 2.905830e-03
sIgE_f2   -3.166320     0.000000e+00  0.029970671    0.000000000  0.27682810 1.543809e-03
sIgE_f4   -3.200752     0.000000e+00  0.035469421    0.000000000  0.32409368 1.370694e-03
sIgE_f1   -4.074880     0.000000e+00  0.016341103    0.000000000  0.11728300 4.603809e-05
sIgE_f20  -4.202133     5.953897e-04  0.051857938    0.004200290  0.35677871 2.644118e-05
sIgE_f3   -5.659508     0.000000e+00  0.003145542    0.000000000  0.01625494 1.518077e-08
sIgE_f17  -5.898697     1.309996e-02  1.174252032    0.085751671  5.75707008 3.663829e-09
bmi2     -11.086278     2.454294e+01 26.106734104    3.443842165  4.12537389 1.462471e-28
age      -17.978175     4.095398e+01 50.409945023   11.988056542 15.38255887 2.888443e-72

$`2`
            v.test Mean in category Overall mean sd in category  Overall sd       p.value
sIgE_f17 24.295775      27.28183602  1.174252032    21.50318294  5.75707008 2.172658e-130
sIgE_f20 18.004145       1.25082112  0.051857938     1.79409828  0.35677871  1.807698e-72
sIgE_f3  13.145783       0.04303023  0.003145542     0.06050838  0.01625494  1.799323e-39
sIgE_f14 12.584599       0.74388945  0.024610767     1.74950012  0.30621284  2.566440e-36
sIgE_f4  12.188176       0.77276852  0.035469421     1.68728552  0.32409368  3.593742e-34
sIgE_f2  10.632950       0.57938296  0.029970671     1.47859712  0.27682810  2.093828e-26
sIgE_f36 10.391927       0.51200563  0.026534870     1.43978253  0.25028371  2.698459e-25
sIgE_f1   7.971785       0.19085300  0.016341103     0.53057583  0.11728300  1.563993e-15
sIgE_f13  7.586510       5.90737712  0.186718716    24.66160243  4.03989038  3.286379e-14
sIgE_f18  6.718500       1.83000093  0.054806598     8.67591954  1.41559548  1.836048e-11
age      -3.632354      39.98074171 50.409945023    14.47841225 15.38255887  2.808478e-04

$`3`
          v.test Mean in category Overall mean sd in category Overall sd      p.value
sIgE_f1 6.071957       0.08282846  0.016341103      0.1880077 0.11728300 1.263605e-09
sIgE_f3 5.789448       0.01193168  0.003145542      0.0200712 0.01625494 7.061804e-09
sIgE_f2 3.046537       0.10871004  0.029970671      0.2244035 0.27682810 2.314938e-03

$`4`
            v.test Mean in category Overall mean sd in category  Overall sd       p.value
age      21.505709     6.264264e+01 50.409945023    9.172829372 15.38255887 1.376644e-102
bmi2     10.726381     2.774301e+01 26.106734104    4.049642119  4.12537389  7.653490e-27
sIgE_f14 -2.173512     0.000000e+00  0.024610767    0.000000000  0.30621284  2.974177e-02
sIgE_f36 -2.763447     9.594175e-04  0.026534870    0.006813830  0.25028371  5.719440e-03
sIgE_f2  -2.927835     0.000000e+00  0.029970671    0.000000000  0.27682810  3.413307e-03
sIgE_f4  -2.959674     0.000000e+00  0.035469421    0.000000000  0.32409368  3.079646e-03
sIgE_f1  -3.767963     0.000000e+00  0.016341103    0.000000000  0.11728300  1.645848e-04
sIgE_f20 -3.876671     7.136078e-04  0.051857938    0.005353473  0.35677871  1.058954e-04
sIgE_f3  -5.233238     0.000000e+00  0.003145542    0.000000000  0.01625494  1.665657e-07
sIgE_f17 -5.469448     9.898991e-03  1.174252032    0.081973061  5.75707008  4.514381e-08

With asthma and Rhinitis Data clusters with DEL (Deep Embedding Clustering layer)

result_as_rh_uft_DEL <- read.csv('/Users/xbasra/Documents/Data/Clustering_Food_Alergies/Intermediate/CsvData_Output/result_as_rh_uft_DEL.csv')
result_as_rh_uft_DEL$farmlive[result_as_rh_uft_DEL$farmlive == ""] <- NA
result_as_rh_uft_DEL <-  result_as_rh_uft_DEL %>% replace_na (list(farmlive = 'no'))
table_as_rh_uft_DEL <- tableby(cluster ~ ., data = as.list(result_as_rh_uft_DEL))
summary(table_as_rh_uft_DEL, title = "Charachtaristcs of Clusters")

Table: Charachtaristcs of Clusters

	0 (N=279)	1 (N=23)	2 (N=670)	3 (N=22)	4 (N=84)	Total (N=1078)	p value
sIgE_f1							< 0.001
Mean (SD)	0.117 (0.622)	3.788 (15.346)	0.002 (0.028)	0.596 (1.096)	0.151 (0.852)	0.136 (2.300)
Range	0.000 - 8.179	0.000 - 73.692	0.000 - 0.626	0.020 - 4.695	0.000 - 7.725	0.000 - 73.692
sIgE_f2							< 0.001
Mean (SD)	0.078 (0.202)	1.035 (3.295)	0.000 (0.006)	2.251 (2.998)	0.072 (0.208)	0.094 (0.728)
Range	0.000 - 1.549	0.000 - 13.623	0.000 - 0.140	0.034 - 13.006	0.000 - 1.338	0.000 - 13.623
sIgE_f3							< 0.001
Mean (SD)	0.013 (0.028)	0.178 (0.391)	0.000 (0.003)	0.255 (0.357)	0.026 (0.064)	0.015 (0.090)
Range	0.000 - 0.213	0.000 - 1.332	0.000 - 0.042	0.015 - 1.080	0.000 - 0.310	0.000 - 1.332
sIgE_f4							< 0.001
Mean (SD)	0.112 (0.319)	1.773 (3.369)	0.001 (0.009)	0.319 (0.370)	0.497 (1.310)	0.112 (0.687)
Range	0.000 - 2.275	0.000 - 12.512	0.000 - 0.224	0.030 - 1.291	0.000 - 7.459	0.000 - 12.512
sIgE_f13							< 0.001
Mean (SD)	0.302 (0.866)	8.824 (27.898)	0.016 (0.079)	1.515 (3.750)	1.329 (5.285)	0.411 (4.497)
Range	0.000 - 11.866	0.000 - 133.659	0.000 - 0.830	0.021 - 16.776	0.000 - 45.700	0.000 - 133.659
sIgE_f14							< 0.001
Mean (SD)	0.048 (0.158)	1.759 (3.429)	0.000 (0.001)	0.225 (0.593)	0.216 (0.729)	0.071 (0.601)
Range	0.000 - 1.184	0.000 - 12.386	0.000 - 0.020	0.000 - 2.785	0.000 - 5.216	0.000 - 12.386
sIgE_f17							< 0.001
Mean (SD)	4.338 (4.800)	44.076 (35.504)	0.077 (0.243)	1.691 (4.311)	10.156 (12.891)	2.937 (9.526)
Range	0.000 - 23.778	0.000 - 111.259	0.000 - 1.619	0.000 - 17.146	0.000 - 39.910	0.000 - 111.259
sIgE_f18							< 0.001
Mean (SD)	0.041 (0.212)	2.301 (9.729)	0.005 (0.071)	0.040 (0.071)	0.069 (0.271)	0.069 (1.436)
Range	0.000 - 2.901	0.000 - 46.879	0.000 - 1.678	0.000 - 0.244	0.000 - 1.770	0.000 - 46.879
sIgE_f20							< 0.001
Mean (SD)	0.173 (0.337)	1.825 (2.624)	0.006 (0.027)	0.214 (0.401)	0.531 (1.317)	0.133 (0.625)
Range	0.000 - 3.469	0.000 - 9.959	0.000 - 0.343	0.000 - 1.686	0.000 - 8.781	0.000 - 9.959
sIgE_f36							< 0.001
Mean (SD)	0.086 (0.155)	0.901 (1.941)	0.007 (0.026)	0.067 (0.120)	0.175 (0.660)	0.061 (0.368)
Range	0.000 - 1.051	0.000 - 7.754	0.000 - 0.277	0.000 - 0.430	0.000 - 5.642	0.000 - 7.754
gender2							0.024
females	149 (53.4%)	14 (60.9%)	396 (59.1%)	7 (31.8%)	40 (47.6%)	606 (56.2%)
males	130 (46.6%)	9 (39.1%)	274 (40.9%)	15 (68.2%)	44 (52.4%)	472 (43.8%)
age							< 0.001
Mean (SD)	44.408 (14.931)	39.107 (15.451)	49.341 (15.383)	51.708 (18.292)	45.759 (14.349)	47.615 (15.443)
Range	19.058 - 77.130	20.741 - 74.510	19.535 - 76.656	21.113 - 76.190	19.415 - 78.075	19.058 - 78.075
bmi2							< 0.001
Mean (SD)	26.516 (4.575)	30.321 (10.071)	25.964 (3.511)	29.757 (4.191)	33.215 (6.604)	26.842 (4.790)
Range	17.915 - 38.725	19.044 - 50.058	17.404 - 34.475	20.809 - 37.545	19.841 - 44.413	17.404 - 50.058
farmlive
	0 (0.0%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	0 (0.0%)
no	254 (91.0%)	23 (100.0%)	599 (89.4%)	20 (90.9%)	72 (85.7%)	968 (89.8%)
yes	25 (9.0%)	0 (0.0%)	71 (10.6%)	2 (9.1%)	12 (14.3%)	110 (10.2%)
family_allergy_hist							0.006
no	106 (38.0%)	10 (43.5%)	324 (48.4%)	8 (36.4%)	27 (32.1%)	475 (44.1%)
yes	173 (62.0%)	13 (56.5%)	346 (51.6%)	14 (63.6%)	57 (67.9%)	603 (55.9%)

# adding the id variable 
#result_food_uft_DEL_k$ID <- food_data_id$ID 
#write.csv(result_food_uft_DEL_k, "/Users/xbasra/Documents/Data/Clustering_Food_Alergies/CsvData/result_food_uft_DEL_k.csv")

Charachtiristic Analysis

result_as_rh_uft_DEL$cluster <- as.factor(result_as_rh_uft_DEL$cluster)
catdes(result_as_rh_uft_DEL, 16)

Without asthma and Rhinitis Data clusters with DEL (Deep Embedding Clustering layer)

result_no_as_rh_uft_DEL <- read.csv('/Users/xbasra/Documents/Data/Clustering_Food_Alergies/Intermediate/CsvData_Output/result_no_as_rh_uft_DEL.csv')
result_no_as_rh_uft_DEL$farmlive[result_no_as_rh_uft_DEL$farmlive == ""] <- NA
result_no_as_rh_uft_DEL <-  result_no_as_rh_uft_DEL %>% replace_na (list(farmlive = 'no'))
table_no_as_rh_uft_DEL <- tableby(cluster ~ ., data = as.list(result_no_as_rh_uft_DEL))
summary(table_no_as_rh_uft_DEL, title = "Charachtaristcs of Clusters")

Table: Charachtaristcs of Clusters

	0 (N=597)	1 (N=148)	2 (N=49)	Total (N=794)	p value
sIgE_f1					< 0.001
Mean (SD)	0.000 (0.000)	0.048 (0.141)	0.010 (0.030)	0.010 (0.064)
Range	0.000 - 0.000	0.000 - 0.918	0.000 - 0.149	0.000 - 0.918
sIgE_f2					< 0.001
Mean (SD)	0.000 (0.000)	0.054 (0.159)	0.066 (0.316)	0.014 (0.106)
Range	0.000 - 0.000	0.000 - 1.091	0.000 - 2.143	0.000 - 2.143
sIgE_f3					< 0.001
Mean (SD)	0.000 (0.000)	0.008 (0.018)	0.008 (0.026)	0.002 (0.011)
Range	0.000 - 0.000	0.000 - 0.067	0.000 - 0.134	0.000 - 0.134
sIgE_f4					< 0.001
Mean (SD)	0.000 (0.000)	0.042 (0.145)	0.174 (0.593)	0.019 (0.164)
Range	0.000 - 0.000	0.000 - 1.129	0.000 - 2.543	0.000 - 2.543
sIgE_f13					< 0.001
Mean (SD)	0.000 (0.000)	0.061 (0.185)	3.170 (21.379)	0.207 (5.315)
Range	0.000 - 0.000	0.000 - 1.596	0.000 - 149.746	0.000 - 149.746
sIgE_f14					< 0.001
Mean (SD)	0.000 (0.000)	0.012 (0.051)	0.156 (0.731)	0.012 (0.185)
Range	0.000 - 0.000	0.000 - 0.366	0.000 - 4.886	0.000 - 4.886
sIgE_f17					< 0.001
Mean (SD)	0.000 (0.000)	0.465 (1.241)	2.520 (7.328)	0.242 (1.977)
Range	0.000 - 0.000	0.000 - 7.065	0.000 - 36.193	0.000 - 36.193
sIgE_f18					< 0.001
Mean (SD)	0.000 (0.000)	0.010 (0.037)	0.036 (0.140)	0.004 (0.039)
Range	0.000 - 0.000	0.000 - 0.322	0.000 - 0.868	0.000 - 0.868
sIgE_f20					< 0.001
Mean (SD)	0.000 (0.000)	0.036 (0.099)	0.141 (0.444)	0.015 (0.122)
Range	0.000 - 0.000	0.000 - 0.606	0.000 - 2.149	0.000 - 2.149
sIgE_f36					< 0.001
Mean (SD)	0.000 (0.000)	0.027 (0.073)	0.058 (0.200)	0.009 (0.061)
Range	0.000 - 0.000	0.000 - 0.406	0.000 - 1.081	0.000 - 1.081
gender2					0.262
females	303 (50.8%)	84 (56.8%)	29 (59.2%)	416 (52.4%)
males	294 (49.2%)	64 (43.2%)	20 (40.8%)	378 (47.6%)
age					0.920
Mean (SD)	50.736 (15.755)	51.145 (14.937)	51.481 (14.445)	50.858 (15.512)
Range	18.146 - 77.746	19.302 - 76.877	22.091 - 74.524	18.146 - 77.746
bmi2					< 0.001
Mean (SD)	24.713 (2.715)	28.662 (3.831)	34.498 (5.473)	26.053 (4.136)
Range	16.975 - 30.653	18.904 - 41.197	22.097 - 46.094	16.975 - 46.094
farmlive
	0 (0.0%)	0 (0.0%)	0 (0.0%)	0 (0.0%)
no	504 (84.4%)	132 (89.2%)	44 (89.8%)	680 (85.6%)
yes	93 (15.6%)	16 (10.8%)	5 (10.2%)	114 (14.4%)
family_allergy_hist					0.089
no	419 (70.2%)	101 (68.2%)	27 (55.1%)	547 (68.9%)
yes	178 (29.8%)	47 (31.8%)	22 (44.9%)	247 (31.1%)

# adding the id variable 
#result_food_uft_DEL_k$ID <- food_data_id$ID 
#write.csv(result_food_uft_DEL_k, "/Users/xbasra/Documents/Data/Clustering_Food_Alergies/CsvData/result_food_uft_DEL_k.csv")

Charachtiristic Analysis

result_no_as_rh_uft_DEL$cluster <- as.factor(result_no_as_rh_uft_DEL$cluster)
catdes(result_no_as_rh_uft_DEL, 16)

adding the id varaible

#resultft_DEL_all$ID <- food_data_id$ID
resultft_DEL_all_5$ID <- food_data_id$ID
result_rand_uft_DEL_k$ID <- rand_food_data_id$ID
result_as_rh_uft_DEL$ID <- as_ri_food_id$ID
result_no_as_rh_uft_DEL$ID <- no_as_ri_food_id$ID
write.csv(resultft_DEL_all,'/Users/xbasra/Documents/Data/Clustering_Food_Alergies/Results/CSVData/resultft_DEL_all_id_5.csv')
write.csv(result_rand_uft_DEL_k,'/Users/xbasra/Documents/Data/Clustering_Food_Alergies/Results/CSVData/result_rand_uft_DEL_k_id.csv')
write.csv(result_as_rh_uft_DEL,'/Users/xbasra/Documents/Data/Clustering_Food_Alergies/Results/CSVData/result_as_rh_uft_DEL_id.csv')
write.csv(result_no_as_rh_uft_DEL,'/Users/xbasra/Documents/Data/Clustering_Food_Alergies/Results/CSVData/result_no_as_rh_uft_DEL_id.csv')